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  pdftitle={Bayesian data analysis},
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  pdfauthor={Aki Vehtari},
  pdfkeywords={Bayesian probability theory, Bayesian inference, Bayesian data analysis},
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\section*{Bayesian data analysis -- reading instructions 9} 
\smallskip
{\bf Aki Vehtari}
\smallskip

\subsection*{Chapter 9}

Outline of the chapter 9
\begin{list}{$\bullet$}{\parsep=0pt\itemsep=2pt}
\item 9.1 Context and basic steps (most important part)
\item 9.2 Example
\item 9.3 Multistage decision analysis (you may skip this example)
\item 9.4 Hierarchical decision analysis (you may skip this example)
\item 9.5 Personal vs. institutional decision analysis (important)
\end{list}

Find all the terms and symbols listed below. When reading the chapter,
write down questions related to things unclear for you or things you
think might be unclear for others. 
\begin{list}{$\bullet$}{\parsep=0pt\itemsep=2pt}
\item decision analysis
\item steps of Bayesian decision analysis 1--4 (p. 238)
\item decision
\item outcome
\item utility function
\item expected utility
\item decision tree
\item summarizing inference
\item model selection
\item individual decision problem
\item institutional decision problem
\end{list}

\subsection*{Simpler examples}

The lectures have simpler examples and discus also some challenges in
selecting utilities or costs.

\subsection*{Model selection as a decision problem}

Chapter 7 discusses how model selection con be considered as a
decision problem.

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